Tabular Classification
Scikit-learn
English
stacking-ensemble
xgboost
catboost
lightgbm
adaboost
randomforest
Eval Results (legacy)
Instructions to use mrsindhunugroho/stacking-ensemble-learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use mrsindhunugroho/stacking-ensemble-learning with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("mrsindhunugroho/stacking-ensemble-learning", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fdb1a5ddba9dff20bda425ca670382dd8a161371e04a6dcd03eccc8a157a12cc
- Size of remote file:
- 637 kB
- SHA256:
- 38e8bf102142df97ff6a4dd2eef9163b82de8e4244a88d8b553953cf61badcbd
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